A hierarchical MPC for multi-objective mixed-integer optimisation applied to redundant refrigeration circuits. Issue 1 (July 2017)

• Record Type: Journal Article
• Authors: Luchini, Elisabeth; Schirrer, Alexander; Kozek, Martin
• Is Part Of: IFAC-PapersOnLine. Volume 50:Issue 1(2017)
• Page Start: 9058
• Page End: 9064
• Publication Date: 2017-07
• Subjects: hierarchical MPC -- mixed-integer optimisation -- multiple sampling rates -- refrigeration system; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2017.08.1629
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Temperature control of an insulated cool box (ICB) can be efficiently provided by model predictive control. However, if the cooling capacity is supplied by redundant refrigeration circuits (RCs) with both continuous and switched control variables, the overall control design becomes complex: 1) Time constants of the ICB and RCs differ by a factor of approximately 100. 2) Switched and continuous control variables require mixed-integer optimisation. 3) Power consumption, wear, control performance and output tracking call for multi-objective optimisation. In this work a global linear Model Predictive Controller (MPC) is designed to compute a desired cooling capacity at a low sampling frequency for a long prediction horizon, while a mixed-integer MPC (MI-MPC) provides the actual cooling capacity utilising a fast sampling frequency and a short prediction horizon. The control concept is presented, a stability prove is given and simulation results demonstrate the performance of the concept.